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<a href="_c_volkovich_yahalom_8cs.html">Go to the documentation of this file.</a><div class="fragment"><pre class="fragment"><a name="l00001"></a>00001 ﻿extern alias <a class="code" href="_c_volkovich_yahalom_8cs.html#adb966b3e984a1965fe3340708abd6850">alglibnet2</a>;
<a name="l00002"></a>00002 
<a name="l00003"></a>00003 <span class="keyword">using</span> System;
<a name="l00004"></a>00004 <span class="keyword">using</span> System.Collections.Generic;
<a name="l00005"></a>00005 <span class="keyword">using</span> System.Linq;
<a name="l00006"></a>00006 <span class="keyword">using</span> System.Text;
<a name="l00007"></a>00007 
<a name="l00008"></a>00008 <span class="keyword">namespace </span>ClusterAggregation.ClusterAggregators
<a name="l00009"></a>00009 {
<a name="l00010"></a>00010     <span class="keyword">using</span> Datum;
<a name="l00011"></a>00011     <span class="keyword">using</span> DataSets;
<a name="l00012"></a>00012     <span class="keyword">using</span> Clusterers;
<a name="l00013"></a>00013     <span class="keyword">using</span> GeneralTools;
<a name="l00014"></a>00014 
<a name="l00020"></a><a class="code" href="class_cluster_aggregation_1_1_cluster_aggregators_1_1_c_volkovich_yahalom.html">00020</a>     <span class="keyword">public</span> <span class="keyword">class </span><a class="code" href="class_cluster_aggregation_1_1_cluster_aggregators_1_1_c_volkovich_yahalom.html">CVolkovichYahalom</a>:<a class="code" href="interface_cluster_aggregation_1_1_cluster_aggregators_1_1_i_consensus.html">IConsensus</a>
<a name="l00021"></a>00021     {
<a name="l00023"></a>00023         <span class="keyword">private</span> <a class="code" href="interface_cluster_aggregation_1_1_clusterers_1_1_i_clusterer.html">IClusterer</a> m_clusterer;
<a name="l00024"></a>00024      
<a name="l00026"></a>00026         <span class="keyword">private</span> <span class="keywordtype">double</span> m_lambda;
<a name="l00027"></a>00027 
<a name="l00033"></a><a class="code" href="class_cluster_aggregation_1_1_cluster_aggregators_1_1_c_volkovich_yahalom.html#ac8c1cf90747ebe9fbc516324935ec40d">00033</a>         <span class="keyword">public</span> <a class="code" href="class_cluster_aggregation_1_1_cluster_aggregators_1_1_c_volkovich_yahalom.html">CVolkovichYahalom</a>(<a class="code" href="interface_cluster_aggregation_1_1_clusterers_1_1_i_clusterer.html">IClusterer</a> arg = null, <span class="keywordtype">double</span> lambda = 1)
<a name="l00034"></a>00034         {
<a name="l00035"></a>00035             m_clusterer = arg;
<a name="l00036"></a>00036             <span class="keywordflow">if</span> (null == m_clusterer)
<a name="l00037"></a>00037             {
<a name="l00038"></a>00038                 <span class="comment">//m_clusterer = new CPamImpl();</span>
<a name="l00039"></a>00039                 m_clusterer = <span class="keyword">new</span> <a class="code" href="class_cluster_aggregation_1_1_clusterers_1_1_c_spectral_clusterer.html">CSpectralClusterer</a>(null, 0.3, <span class="keyword">true</span>);
<a name="l00040"></a>00040             }
<a name="l00041"></a>00041 
<a name="l00042"></a>00042             m_lambda = lambda;
<a name="l00043"></a>00043             <span class="keywordflow">if</span> (lambda &lt;= 0)
<a name="l00044"></a>00044             {
<a name="l00045"></a>00045                 m_lambda = 1;
<a name="l00046"></a>00046             }            
<a name="l00047"></a>00047         }
<a name="l00048"></a>00048 
<a name="l00049"></a><a class="code" href="class_cluster_aggregation_1_1_cluster_aggregators_1_1_c_volkovich_yahalom.html#a39d129abb2f388d7825c851cdb018af1">00049</a>         <span class="keyword">public</span> <a class="code" href="class_cluster_aggregation_1_1_data_sets_1_1_c_partition.html">CPartition</a> ensemble(<a class="code" href="class_cluster_aggregation_1_1_data_sets_1_1_c_partition.html">CPartition</a>[] partitions, <a class="code" href="class_cluster_aggregation_1_1_datum_1_1_a_data.html">AData</a>[] data, <span class="keywordtype">int</span> k)
<a name="l00050"></a>00050         {
<a name="l00051"></a>00051             <span class="keywordtype">int</span> n = data.Length;
<a name="l00052"></a>00052             <span class="keywordtype">double</span>[,] aggregatedR = <span class="keyword">new</span> <span class="keywordtype">double</span>[n, n];
<a name="l00053"></a>00053             <span class="keywordtype">double</span>[,] Ri = <span class="keyword">new</span> <span class="keywordtype">double</span>[n, n];
<a name="l00054"></a>00054 
<a name="l00055"></a>00055             <a class="code" href="class_cluster_aggregation_1_1_general_tools_1_1_c_matrix_operators.html">CMatrixOperators</a>.<a class="code" href="class_cluster_aggregation_1_1_general_tools_1_1_c_matrix_operators.html#a2184af25d12d363c504da25d6ce6b3cd">resetMat</a>(ref aggregatedR, n, n); <span class="comment">// initiate R</span>
<a name="l00056"></a>00056 
<a name="l00057"></a>00057             <span class="keywordflow">foreach</span> (<a class="code" href="class_cluster_aggregation_1_1_data_sets_1_1_c_partition.html">CPartition</a> p <span class="keywordflow">in</span> partitions)
<a name="l00058"></a>00058             {
<a name="l00059"></a>00059                 calculateRi(ref Ri, data, n, p);
<a name="l00060"></a>00060                 <a class="code" href="class_cluster_aggregation_1_1_general_tools_1_1_c_matrix_operators.html">CMatrixOperators</a>.<a class="code" href="class_cluster_aggregation_1_1_general_tools_1_1_c_matrix_operators.html#ac4b1a9e8f2c171f02875080adcdb8231">addToFirst</a>(ref aggregatedR, Ri, n, n);
<a name="l00061"></a>00061             }
<a name="l00062"></a>00062             <a class="code" href="class_cluster_aggregation_1_1_general_tools_1_1_c_matrix_operators.html">CMatrixOperators</a>.<a class="code" href="class_cluster_aggregation_1_1_general_tools_1_1_c_matrix_operators.html#a029622a416132aea9d256a38e19e6bb9">divMat</a>(ref aggregatedR, n, n, partitions.Length);
<a name="l00063"></a>00063        
<a name="l00064"></a>00064             <a class="code" href="class_cluster_aggregation_1_1_datum_1_1_c_matrix_based_distance.html">CMatrixBasedDistance</a> distfunc = <span class="keyword">new</span> <a class="code" href="class_cluster_aggregation_1_1_datum_1_1_c_matrix_based_distance.html">CMatrixBasedDistance</a>(aggregatedR);
<a name="l00065"></a>00065            
<a name="l00066"></a>00066             <a class="code" href="class_cluster_aggregation_1_1_data_sets_1_1_c_partition.html">CPartition</a> tmp = m_clusterer.cluster(data,distfunc,k);
<a name="l00067"></a>00067             tmp.<a class="code" href="class_cluster_aggregation_1_1_data_sets_1_1_c_partition.html#a1be9e2847752c965f383b344318065b7">name</a> = <span class="stringliteral">&quot;Volkovich-Yahalom&quot;</span>;
<a name="l00068"></a>00068             tmp.<a class="code" href="class_cluster_aggregation_1_1_data_sets_1_1_c_partition.html#ab47f8f65306a645f0ce17581643115bd">ANMI</a> = tmp.<a class="code" href="class_cluster_aggregation_1_1_data_sets_1_1_c_partition.html#aa8487de094410cfdf6bfeec93019bc91">compareTo</a>(partitions);
<a name="l00069"></a>00069             <span class="keywordflow">return</span> tmp;
<a name="l00070"></a>00070         }
<a name="l00071"></a>00071 
<a name="l00079"></a><a class="code" href="class_cluster_aggregation_1_1_cluster_aggregators_1_1_c_volkovich_yahalom.html#ad02fff1956827f9932d86897d11d1c4a">00079</a>         <span class="keyword">public</span> <span class="keywordtype">void</span> calculateRi(ref <span class="keywordtype">double</span>[,] R, <a class="code" href="class_cluster_aggregation_1_1_datum_1_1_a_data.html">AData</a>[] data, <span class="keywordtype">int</span> n, <a class="code" href="class_cluster_aggregation_1_1_data_sets_1_1_c_partition.html">CPartition</a> p)
<a name="l00080"></a>00080         {
<a name="l00081"></a>00081             <span class="keywordtype">int</span> d = data[0].<a class="code" href="class_cluster_aggregation_1_1_datum_1_1_a_data.html#a0aed3fd634fcb713a8cfdf9f5a8d8d96">coordinates</a>.Length;
<a name="l00082"></a>00082             <span class="keywordtype">int</span> C = p.<a class="code" href="class_cluster_aggregation_1_1_data_sets_1_1_c_partition.html#a749d3edca2897d2127ce95934648d3ea">clusters</a>.Count();
<a name="l00083"></a>00083             <span class="keywordtype">double</span>[,] A = <span class="keyword">new</span> <span class="keywordtype">double</span>[d, d];
<a name="l00084"></a>00084             <span class="keywordtype">double</span>[,] covMat= <span class="keyword">new</span> <span class="keywordtype">double</span>[d, d];
<a name="l00085"></a>00085             <span class="keywordtype">double</span>[,] tmp = <span class="keyword">new</span> <span class="keywordtype">double</span>[d, d];
<a name="l00086"></a>00086             <span class="keywordtype">double</span>[,] Zi = <span class="keyword">new</span> <span class="keywordtype">double</span>[n, C];
<a name="l00087"></a>00087             <a class="code" href="_c_volkovich_yahalom_8cs.html#adb966b3e984a1965fe3340708abd6850">alglibnet2</a>.alglib.matinvreport rep;
<a name="l00088"></a>00088             <span class="keywordtype">int</span> info;
<a name="l00089"></a>00089 
<a name="l00090"></a>00090             <a class="code" href="class_cluster_aggregation_1_1_general_tools_1_1_c_matrix_operators.html">CMatrixOperators</a>.<a class="code" href="class_cluster_aggregation_1_1_general_tools_1_1_c_matrix_operators.html#a2184af25d12d363c504da25d6ce6b3cd">resetMat</a>(ref R, n, n);
<a name="l00091"></a>00091             <a class="code" href="class_cluster_aggregation_1_1_general_tools_1_1_c_matrix_operators.html">CMatrixOperators</a>.<a class="code" href="class_cluster_aggregation_1_1_general_tools_1_1_c_matrix_operators.html#a2184af25d12d363c504da25d6ce6b3cd">resetMat</a>(ref tmp, d, d);
<a name="l00092"></a>00092             <a class="code" href="class_cluster_aggregation_1_1_general_tools_1_1_c_matrix_operators.html">CMatrixOperators</a>.<a class="code" href="class_cluster_aggregation_1_1_general_tools_1_1_c_matrix_operators.html#a2184af25d12d363c504da25d6ce6b3cd">resetMat</a>(ref A, d, d);
<a name="l00093"></a>00093             <a class="code" href="class_cluster_aggregation_1_1_general_tools_1_1_c_matrix_operators.html">CMatrixOperators</a>.<a class="code" href="class_cluster_aggregation_1_1_general_tools_1_1_c_matrix_operators.html#a2184af25d12d363c504da25d6ce6b3cd">resetMat</a>(ref Zi, n, C);
<a name="l00094"></a>00094 
<a name="l00095"></a>00095             
<a name="l00096"></a>00096             <span class="keywordflow">for</span> (<span class="keywordtype">int</span> j = 0; j &lt; C; j++)
<a name="l00097"></a>00097             {
<a name="l00098"></a>00098 
<a name="l00099"></a>00099                 <span class="keywordtype">int</span> clsSize = p.<a class="code" href="class_cluster_aggregation_1_1_data_sets_1_1_c_partition.html#a749d3edca2897d2127ce95934648d3ea">clusters</a>[j].data.Count();
<a name="l00100"></a>00100                 <span class="keywordtype">double</span> tmpSmoother = m_lambda / (m_lambda + clsSize);
<a name="l00101"></a>00101 
<a name="l00102"></a>00102                 <span class="keywordtype">double</span>[,] clsMat = <span class="keyword">new</span> <span class="keywordtype">double</span>[p.<a class="code" href="class_cluster_aggregation_1_1_data_sets_1_1_c_partition.html#a749d3edca2897d2127ce95934648d3ea">clusters</a>[j].data.Count(), d];
<a name="l00103"></a>00103                 <a class="code" href="class_cluster_aggregation_1_1_general_tools_1_1_c_matrix_operators.html">CMatrixOperators</a>.<a class="code" href="class_cluster_aggregation_1_1_general_tools_1_1_c_matrix_operators.html#a2184af25d12d363c504da25d6ce6b3cd">resetMat</a>(ref clsMat, p.<a class="code" href="class_cluster_aggregation_1_1_data_sets_1_1_c_partition.html#a749d3edca2897d2127ce95934648d3ea">clusters</a>[j].data.Count(), d);
<a name="l00104"></a>00104                 <a class="code" href="class_cluster_aggregation_1_1_general_tools_1_1_c_matrix_operators.html">CMatrixOperators</a>.<a class="code" href="class_cluster_aggregation_1_1_general_tools_1_1_c_matrix_operators.html#a2184af25d12d363c504da25d6ce6b3cd">resetMat</a>(ref covMat, d, d);
<a name="l00105"></a>00105 
<a name="l00106"></a>00106                 <span class="comment">// calculate Xi</span>
<a name="l00107"></a>00107                 <a class="code" href="class_cluster_aggregation_1_1_datum_1_1_a_data.html">AData</a> Xi = <span class="keyword">new</span> <a class="code" href="class_cluster_aggregation_1_1_datum_1_1_a_data.html">AData</a>(p.<a class="code" href="class_cluster_aggregation_1_1_data_sets_1_1_c_partition.html#a749d3edca2897d2127ce95934648d3ea">clusters</a>[0].data[0].coordinates.Length);
<a name="l00108"></a>00108                 Xi.<a class="code" href="class_cluster_aggregation_1_1_datum_1_1_a_data.html#a06a02472d402641578197283b97e0a19">zerodize</a>();
<a name="l00109"></a>00109 
<a name="l00110"></a>00110                 <span class="keywordflow">foreach</span> (<a class="code" href="class_cluster_aggregation_1_1_datum_1_1_a_data.html">AData</a> datum <span class="keywordflow">in</span> p.<a class="code" href="class_cluster_aggregation_1_1_data_sets_1_1_c_partition.html#a749d3edca2897d2127ce95934648d3ea">clusters</a>[j].data)
<a name="l00111"></a>00111                 {
<a name="l00112"></a>00112                     Xi.accumulate(datum,p.<a class="code" href="class_cluster_aggregation_1_1_data_sets_1_1_c_partition.html#a749d3edca2897d2127ce95934648d3ea">clusters</a>[j].data.Count());
<a name="l00113"></a>00113                 }
<a name="l00114"></a>00114 
<a name="l00115"></a>00115                 <span class="comment">// for current cluster we have specific Xi</span>
<a name="l00116"></a>00116                 <span class="comment">// calc tmp = Xi Xit</span>
<a name="l00117"></a>00117                 <a class="code" href="class_cluster_aggregation_1_1_general_tools_1_1_c_matrix_operators.html">CMatrixOperators</a>.<a class="code" href="class_cluster_aggregation_1_1_general_tools_1_1_c_matrix_operators.html#a2184af25d12d363c504da25d6ce6b3cd">resetMat</a>(ref tmp, d, d);
<a name="l00118"></a>00118 
<a name="l00119"></a>00119                 <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; d; i++)
<a name="l00120"></a>00120                 {    
<a name="l00121"></a>00121                     <span class="keywordflow">for</span> (<span class="keywordtype">int</span> l = 0; l &lt; d; l++)
<a name="l00122"></a>00122                     {
<a name="l00123"></a>00123                         tmp[i, l] = Xi.coordinates[i] * Xi.coordinates[l];
<a name="l00124"></a>00124                     }
<a name="l00125"></a>00125                 }
<a name="l00126"></a>00126 
<a name="l00127"></a>00127                 <span class="comment">// calculate covariance matrix</span>
<a name="l00128"></a>00128                 <a class="code" href="_c_volkovich_yahalom_8cs.html#adb966b3e984a1965fe3340708abd6850">alglibnet2</a>.alglib.covm(tmp, out covMat);
<a name="l00129"></a>00129 
<a name="l00130"></a>00130                 <span class="comment">// add (tmp = Xi Xit) to A - never forgetting to mult by clsSize!</span>
<a name="l00131"></a>00131 
<a name="l00132"></a>00132                 <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; d; i++)
<a name="l00133"></a>00133                 {
<a name="l00134"></a>00134                     <span class="keywordflow">for</span> (<span class="keywordtype">int</span> l = 0; l &lt; d; l++)
<a name="l00135"></a>00135                     {
<a name="l00136"></a>00136                         A[i, l] += clsSize * ( covMat[i, l] + tmpSmoother * tmp[i, l]);
<a name="l00137"></a>00137                     }
<a name="l00138"></a>00138                 }
<a name="l00139"></a>00139 
<a name="l00140"></a>00140 
<a name="l00141"></a>00141             } <span class="comment">// end of calc Ai ^ -1</span>
<a name="l00142"></a>00142 
<a name="l00143"></a>00143 
<a name="l00144"></a>00144             <span class="comment">//Ai ^ -1</span>
<a name="l00145"></a>00145             <a class="code" href="_c_volkovich_yahalom_8cs.html#adb966b3e984a1965fe3340708abd6850">alglibnet2</a>.alglib.spdmatrixinverse(ref A, out info, out rep);
<a name="l00146"></a>00146 
<a name="l00147"></a>00147             tmp = <span class="keyword">new</span> <span class="keywordtype">double</span>[d, n];
<a name="l00148"></a>00148             <a class="code" href="class_cluster_aggregation_1_1_general_tools_1_1_c_matrix_operators.html">CMatrixOperators</a>.<a class="code" href="class_cluster_aggregation_1_1_general_tools_1_1_c_matrix_operators.html#a2184af25d12d363c504da25d6ce6b3cd">resetMat</a>(ref tmp, d, n);
<a name="l00149"></a>00149 
<a name="l00150"></a>00150             <span class="comment">// calc Xt</span>
<a name="l00151"></a>00151             <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; n; i++)
<a name="l00152"></a>00152             {
<a name="l00153"></a>00153                 <span class="keywordflow">for</span> (<span class="keywordtype">int</span> j = 0; j &lt; d; j++)
<a name="l00154"></a>00154                 {
<a name="l00155"></a>00155                     tmp[j, i] = data[i].<a class="code" href="class_cluster_aggregation_1_1_datum_1_1_a_data.html#a0aed3fd634fcb713a8cfdf9f5a8d8d96">coordinates</a>[j];
<a name="l00156"></a>00156                 }
<a name="l00157"></a>00157             }
<a name="l00158"></a>00158             <span class="comment">//TODO: calc X, then do a mult function for A * B, and use to calc Ri = X * A * Xt</span>
<a name="l00159"></a>00159 
<a name="l00160"></a>00160             <a class="code" href="class_cluster_aggregation_1_1_general_tools_1_1_c_matrix_operators.html">CMatrixOperators</a>.<a class="code" href="class_cluster_aggregation_1_1_general_tools_1_1_c_matrix_operators.html#aebe4eb0fd81c6a44553d4a4f7e006859">multMatrices</a>(out covMat, A, tmp, d, d, n);
<a name="l00161"></a>00161 
<a name="l00162"></a>00162             tmp = <span class="keyword">new</span> <span class="keywordtype">double</span>[n, d];
<a name="l00163"></a>00163             <a class="code" href="class_cluster_aggregation_1_1_general_tools_1_1_c_matrix_operators.html">CMatrixOperators</a>.<a class="code" href="class_cluster_aggregation_1_1_general_tools_1_1_c_matrix_operators.html#a2184af25d12d363c504da25d6ce6b3cd">resetMat</a>(ref tmp, n, d);
<a name="l00164"></a>00164 
<a name="l00165"></a>00165             <span class="comment">// calc X</span>
<a name="l00166"></a>00166             <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; n; i++)
<a name="l00167"></a>00167             {
<a name="l00168"></a>00168                 <span class="keywordflow">for</span> (<span class="keywordtype">int</span> j = 0; j &lt; d; j++)
<a name="l00169"></a>00169                 {
<a name="l00170"></a>00170                     tmp[i, j] = data[i].<a class="code" href="class_cluster_aggregation_1_1_datum_1_1_a_data.html#a0aed3fd634fcb713a8cfdf9f5a8d8d96">coordinates</a>[j];
<a name="l00171"></a>00171                 }
<a name="l00172"></a>00172             }
<a name="l00173"></a>00173 
<a name="l00174"></a>00174             <a class="code" href="class_cluster_aggregation_1_1_general_tools_1_1_c_matrix_operators.html">CMatrixOperators</a>.<a class="code" href="class_cluster_aggregation_1_1_general_tools_1_1_c_matrix_operators.html#aebe4eb0fd81c6a44553d4a4f7e006859">multMatrices</a>(out R, tmp, covMat, n, d, n);
<a name="l00175"></a>00175 
<a name="l00176"></a>00176         }
<a name="l00177"></a>00177     }
<a name="l00178"></a>00178 }
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